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Machine Learning for Protein Subcellular Localization Prediction

Comprehensively covers protein subcellular localization from single-label prediction to multi-label prediction, and includes prediction;

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Practical Bioinformatician, The

of computational prediction of protein cellular localization, and selected discussions of inference of protein function.* Overview of methods for;

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Practical Bioinformatician, The

of computational prediction of protein cellular localization, and selected discussions of inference of protein function.* Overview of methods for;

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Machine Learning based Natural Scene Recognition for Mobile Robot Localization i

This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene;

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Protein Bioinformatics

prediction in the protein structure. The aim of this book is to describe hybrid methods that have been developed in order to solve the problem;

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Intelligent Computing Theories and Application

Interaction Prediction; Protein Structure and Function Prediction; Next-Gen Sequencing and Metagenomics; Structure Prediction and Folding; Biomarker;

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Machine Learning Modeling for IoUT Networks

transmission, localization and positioning, machine learning modeling for underwater communication, and ongoing challenges in the field. In addition;

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Protein Structure Prediction

This thorough new edition explores web servers and software for protein structure prediction and modeling that are freely available to the;

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Data Analytics in Bioinformatics

learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are;

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Implementations and Applications of Machine Learning

discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data;

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Implementations and Applications of Machine Learning

discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data;

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Prediction of Protein Structures, Functions, and Interactions

for predicting the functions of proteins that have been deduced by sequence analysis and lack experimental characterization. Prediction;

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Machine Learning in Bioinformatics

-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine;

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Machine Learning Deep Learning and Computational Intelligence for Wireless Comm

This book is a collection of best selected research papers presented at the Conference on Machine Learning, Deep Learning and Computational;

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Intelligent Learning Systems

, the computational learning theory, and the use of statistics for the purpose of learning - based on previously available data.Extremely;

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Conformal Prediction for Reliable Machine Learning

financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory;

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Deep Learning in Bioinformatics

, protein structure prediction, gene expression regulation, protein classification, biomedical image processing and diagnosis, biomolecule;

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Carotenoids: Carotenoid and Apocarotenoid Biosynthesis, Metabolic Engineering and Synthetic Biology

protoplasts as a suitable method for protein subcellular localization, High throughput production and characterization of carotenoid enzymes for;

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Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind;

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Cooperative Robots and Sensor Networks

existing solutions that deal with connectivity prediction, and proposed a genetic machine learning approach for link-quality prediction. The third;

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Grammar Based Feature Generation for Time Series Prediction

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation;

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New Approaches of Protein Function Prediction from Protein Interaction Networks

book helps users understand the computational approaches that have been rapidly developed for protein function prediction.;

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Reviews in Computational Chemistry

Mechanics Force Fields for the Everyday Chemist * Machine Learning in Materials Science: Recent Progress and Emerging Applications * Discovering;

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Algorithmic Learning in a Random World

This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s. The main feature;

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Prediction Of Diabetes Blood Sugar Levels Using Machine Learning

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Applied Genetic Programming and Machine Learning

Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly;

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Applied Genetic Programming and Machine Learning

Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly;

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